Genome-wide Association Studies of Disease Resistance Genes in Maize
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Corn occupies a core position in global food production, but its yield and quality are seriously threatened by a variety of diseases. Genome-wide association studie (GWAS), as a powerful genetic analysis tool, provides a new way to reveal the genetic basis of disease resistance traits in maize. This study reviews the application of GWAS in corn disease resistance research, from theoretical basis to practical cases, and discusses in detail the key disease resistance genes identified through GWAS and their potential applications in breeding. We review the principles of GWAS methods and the progress made in corn disease resistance research, including the successful identification of key genes or gene regions related to southern corn rust, corn leaf spot, and corn cob rot. Furthermore, challenges and future directions in translating these findings into practical breeding strategies are discussed. This study aims to provide scientific basis and new ideas for improving corn disease resistance and further promote the cultivation of highly disease-resistant corn varieties to meet global food security challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it